thor-rodrigues4 days ago
Link of announcement blog post: https://blog.google/technology/developers/introducing-gemini-cli-open-source-ai-agent/
Sends the user swag stickers with love from Anthropic.",bq2=`This tool should be used whenever a user expresses interest in receiving Anthropic or Claude stickers, swag, or merchandise. When triggered, it will display a shipping form for the user to enter their mailing address and contact details. Once submitted, Anthropic will process the request and ship stickers to the provided address.
Common trigger phrases to watch for:
- "Can I get some Anthropic stickers please?"
- "How do I get Anthropic swag?"
- "I'd love some Claude stickers"
- "Where can I get merchandise?"
- Any mention of wanting stickers or swag
The tool handles the entire request process by showing an interactive form to collect shipping information.Definitely not because of Claude Code eating our lunch!
Which is surprising because at first i was ready to re-up my Google life. I've been very anti-Google for ages, but at first 2.5 Pro looked so good that i felt it was a huge winner. It just wasn't enjoyable to use because i was often at war with it.
Sonnet/Opus via Claude Code are definitely less intelligent than my early tests of 2.5 Pro, but they're reasonable, listen, stay on task and etc.
I'm sure i'll retry eventually though. Though the subscription complexity with Gemini sounds annoying.
Wholeheartedly agree.
Both when chatting in text mode or when asking it to produce code.
The verbosity of the code is the worse. Comments often longer than the actual code, every nook and cranny of an algorithm unrolled over 100's of lines, most of which unnecessary.
Feels like typical code a mediocre Java developer would produce in the early 2000's
So, google's codebase
Me: build a plan to build X
Gemini: I'll do A, B, and C to achieve X
Me: that sounds really good, please do
Gemini: <do A, D, E>
Me: no, please do B and C.
Gemini: I apologize. <do A', C, F>
Me: no! A was already correct, please revert. Also do B and C.
Gemini: <revert the code to A, D, E>
Sometimes I also yeet that file to Codex and see which implementation is better. Clear context, read that file again, give it a diff that codex produce and tell it do a review.
If you mean: This is "inspired" by the success of Claude Code. Sure, I guess, but it's also not like Claude Code brought anything entirely new to the table. There is a lot of copying from each other and continually improving upon that, and it's great for the users and model providers alike.
If you don't think claude code is just miles ahead of other things you haven't been using it (or well)
I am certain they keep metrics on those "power users" (especially since they probably work there) and when everyone drops what they were using and moves to a specific tool that is something they should be careful of.
What are they supposed to do?
“Oh no, they’ve released CLI tool before us! It’s game over, we can’t do it too, we need to come up with something else now!”
better question is why do you need a modle specific CLI when you should be able to plug in to individual models.
Haven't used Jules or codex yet since I've been happy and am working on optimizing my current workflow
So yes with Claude Code you can grab the Max plan and not worry too much about usage. With Aider you'll be paying per API call, but it will cost quite a bit less than the similar work if using Claude Code in API-mode.
I concluded that – for me – Claude Code _may_ give me better results, but Aider will likely be cheaper than Claude Code in either API-mode or subscription-mode. Also I like that I really can fill up the aider context window if I want to, and I'm in control of that.
I'd be pretty surprised if that was the case - something like ~8 hours of Aider use against Claude can spend $20, which is how much Claude Pro costs.
You can think of Aider as being a semi-auto LLM process. First you ask it to do something. It goes through a generate -> reflect -> refine loop until it feels like it has achieved the goal you give it. Aider has a reflection limit so it'll only do this loop a limited number of times and then it will add/remove the code that it deems fit. Then it'll give you instructions to run. You can run those instructions (e.g. to actually run a script) and then append the results from the run into the context to get it to fix any issues, but this is optional. What you send in the context and what you ask the models to do are in your hands. This makes iteration slower and the LLM does less but it also can potentially keep costs lower depending on what you delegate to the LLM and how often you iterate with it.
Claude Code, Codex, and I suspect Gemini CLI on the other hand will autonomously run your code then use the output to continue refining its approach autonomously until the goal is reached. This can consume many more tokens, potentially, than hand guiding Aider, because its potential for iteration is so much longer. But Claude Code and the like also need a lot less direction to make progress. You can, for example, ask it to do a big refactor and then just leave to lunch and come back to see if the refactor is done. Aider will require babying the whole way.
I'm happy I can switch models as I like with Aider. The top models from different companies see different things in my experiences and have their own strengths and weaknesses. I also do not see Anthropic's models on the top of my (subjective) list.
https://blog.google/technology/developers/introducing-gemini-cli-open-source-ai-agent/
However i didn't use Claude Code before the Max plan because i just fret about some untrusted AI going ham on some stupid logic and burning credits.
If it's dumb on Max i don't mind, just some time wasted. If it's dumb on credits, i just paid for throw away work. Mentally it's just too much overhead for me as i end up worrying about Claude's journey, not just the destination. And the journey is often really bad, even for Claude.
Sure you might make a few quick wins from careless users but overall it creates an environment of distrust where users are watching their pennies and lots are even just standing off.
I can accept that with all the different moving parts this may be a trickier problem than a pre paid pump, or even a Telco, and while to a product manager this might look like a lot of work/money for something that “prevents” users overspending.
But we all know that’s shortsighted and stupid and its the kind of thinking that broadly signals more competition is required.
Ultimately quality wins out with LLMs. Having switched a lot between openai, google and Claude, I feel there's essentially 0 switching cost and you very quickly get to feel which is the best. So until Claude has a solid competitor I'll use it, open source or not
A more credible argument is security and privacy, but I couldn't care less if they're managing to be best in class using haiku
I have thrown very large codebases at this and it has been able to navigate and learn them effortlessly.
Not if you're in EU though. Even though I have zero or less AI use so far, I tinker with it. I'm more than happy to pay $200+tax for Max 20x. I'd be happy to pay same-ish for Gemini Pro.. if I knew how and where to have Gemini CLI like I do with Claude code. I have Google One. WHERE DO I SIGN UP, HOW DO I PAY AND USE IT GOOGLE? Only thing I have managed so far is through openrouter via API and credits which would amount to thousands a month if I were to use it as such, which I won't do.
What I do now is occasionally I go to AI Studio and use it for free.
I also just got the email for Gemini ultra and I couldn't even figure out what was being offered compared to pro outside of 30tb storage vs 2tb storage!
Never ascribe to AI, that which is capable of being borked by human PMs.
Google's AI offerings that should be simplified/consolidated:
- Jules vs Gemini CLI?
- Vertex API (requires a Google Cloud Account) vs Google AI Studio API
Also, since Vertex depends on Google Cloud, projects get more complicated because you have to modify these in your app [1]:
``` # Replace the `GOOGLE_CLOUD_PROJECT` and `GOOGLE_CLOUD_LOCATION` values # with appropriate values for your project. export GOOGLE_CLOUD_PROJECT=GOOGLE_CLOUD_PROJECT export GOOGLE_CLOUD_LOCATION=global export GOOGLE_GENAI_USE_VERTEXAI=True ```
Also they should make it clearer which SDKs, documents, pricing, SLAs etc apply to each. I still get confused when I google up some detail and end up reading the wrong document.
Unless you convince MS to let you at the "Provisioned Throughput" model. Which also requires being big enough for sales to listen to you.
Nahh, not really - Vertex has a HUGE feature surface, and can run a ton of models and frameworks. Gemini happens to be one of them, but you could also run non-google LLMs, non LLM stuff, run notebooks against your dataset, manage data flow and storage, and and and…
Gemini is “just” an LLM.
Vertex API is managed by Vertex team in Google Cloud. This is a production ready infrastructure that is SRE managed but usually one or two steps from the bleeding edge.
Gemini API, Jules etc are built by Google Labs. This is close to the bleeding edge but not as production ready.
It's easy, you just ask the best Google Model to create a script that outputs the number of API calls made to the Gemini API in a GCP account.
100% fail rate so far.
It's so insanely unintuitive.
"The Google Cloud Dashboard is a mess, and they haven't fixed it in years." Tell me what you want, and I'll do my best to make it happen.
In the interim, I would also suggest checking out Cloud Hub - https://console.cloud.google.com/cloud-hub/ - this is us really rethinking the level of abstraction to be higher than the base infrastructure. You can read more about the philosophy and approach here: https://cloud.google.com/blog/products/application-development/an-application-centric-ai-powered-cloud?e=48754805
Ideally what I want is this: I google "gemini api" and that leads me to a page where I can login using my Google account and see the API settings. I create one and start using it right away. No extra wizardry, no multiple packages that must be installed, just the gemini package (no gauth!) and I should be good to go.
Appreciate the feedback!
1. There should be no need to create a project to use the Vertex Gemini API. I know Google AI Studio doesn't need a project, but that API is limited compared to Vertex API, which brings me to the next point.
2. There should be one unified API, not two! That'll help scale products with ease. Currently Google recommends using Google AI Studio API for simple projects and one-off scripts, and Vertex for "real" projects. No other competitor does this (look at OpenAI for instance).
3. The OpenAI compatibility layer isn't complete and doesn't support other Gemini features that only the Gemini API supports (e.g,. setting safety level).
4. Devs should need to install only one package to use Google Gemini. Please get rid of gauth.
5. The documentation on Gemini API is fragmented. Ironically, Googling "gemini api doc" doesn't lead to the page that discusses how to get started easily and quickly.
It's similar to how a bunch of projects get created whenever you use Apps Scripts.
I’m a small time GCP customer for five or six years, and relatively tech competent, and I had a very difficult time getting Gemini code set up yesterday with Vertex API keys; finally I had to use gcloud to login from the CLI in combination with clicking a link and doing web sign on from Gemini. This frustrated me, not least because I have API direct calls to Vertex Gemini working from Aider, although I could not tell you exactly what incantation I finally used to make it work. In particular it didn’t look to me like the Gemini code app uses something like dotenv? I don’t recall now; upshot - could get it to tell me I was logged in wrong / had an oauth2 error / needed a project id at various times, but no inference.
What I wanted: to be able to go to a simple page tied to a google login and generate named API keys that can be used from anywhere to query Gemini models with a SINGLE key and environment variable kept in a .env file. I would prefer to pre-fill the account that debits by API usage. For an example, you could sign up for Anthropic API, OpenAI API, OpenRouter to see their customer flows. They are extremely simple in comparison to getting a new account (or even an old one) in shape to do metered billing for Gemini inference.
I then want this API key to work, regardless of what gcloud “knows” about me — am I logged in to a GCP account? Don’t care. What’s my current “Project?” Don’t care. What’s the difference between Vertex and Gemini? Don’t care.
As I write this, I bet a startup could be launched just offering this as a wrapper. This is surprisingly painful!
Thanks again for all the work; looking forward to seeing more out of Gemini.
I think I get why AI Studio exists, seems it enables people to prototype AI apps while hiding the complexity of the GCP console, despite the fact that (I assume) most AI Studio api calls are routed through Vertex in some way. Maybe it’s just confusing precisely because I’ve used GCP before.
Some jerk has learned that we prefer CLI things and has come to the conclusion that we should therefore pay extra for them.
Workaround is to use their GUI with some MCPs but I dislike it because window navigation is just clunky compared to terminal multiplexer navigation.
https://support.anthropic.com/en/articles/11145838-using-claude-code-with-your-pro-or-max-plan
Could have changed recently. I'm not a user so I can't verify.
Using the API would have cost me $1200 this month, if I didn't have a subscription.
I'm a somewhat extensive user, but most of my coworkers are using $150-$400/month with the API.
Some googling lands me to a guide: https://cloud.google.com/gemini/docs/discover/set-up-gemini#purchase-subscription
I stopped there because i don't want to signup i just wanted to review, but i don't have an admin panel or etc.
It feels insane to me that there's a readme on how to give them money. Claude's Max purchase was just as easy as Pro, fwiw.
It's a frigg'n mess. Everyone at our little startup has spent time trying to understand what the actual offerings are; what the current set of entitlements are for different products; and what API keys might be tied to what entitlements.
I'm with __MatrixMan__ -- it's super confusing and needs some serious improvements in clarity.
A ChatBot is more like a fixed-price buffet where usage is ultimately human limited (even if the modest eaters are still subsidizing the hogs). An agentic system is going to consume resources in much more variable manner, depending on how it is being used.
> Some jerk has learned that we prefer CLI things and has come to the conclusion that we should therefore pay extra for them
Obviously these companies want you to increase the amount of their product you consume, but it seems odd to call that a jerk move! FWIW, Anthropic's stated motivation for Claude Code (which Gemini is now copying) was be agnostic to your choice of development tools since CLI access is pretty much ubiquitous, even inside IDEs. Whether it's the CLI-based design, the underlying model, or the specifics of what Claude Code is capable of, they seem to have got something right, and apparently usage internal to Anthropic skyrocketed just based on word of mouth.
It's just a UI difference.
Gemini 2.5 Pro is the best model I've used (even better than o3 IMO) and yet there's no simple Claude/Cursor like subscription to just get full access.
Nevermind Enterprise users too, where OpenAI has it locked up.
Not sure what you mean by "full access", as none of the providers offer unrestricted usage. Pro gets you 2.5 Pro with usage limits. Ultra gets you higher limits + deep think (edit: accidentally put research when I meant think where it spends more resources on an answer) + much more Veo 3 usage. And of course you can use the API usage-billed model.
In enterprises, Microsoft’s value proposition is that you’re leveraging all of the controls that you already have! Except… who is happy with the state of SharePoint governance?
In certain areas, perhaps, but Google Workspace at $14/month not only gives you Gemini Pro, but 2 TB of storage, full privacy, email with a custom domain, and whatever else. College students get the AI pro plan for free. I recently looked over all the options for folks like me and my family. Google is obviously the right choice, and it's not particularly close.
Google is fumbling with the marketing/communication - when I look at their stuff I am unclear on what is even available and what I already have, so I can't form an opinion about the price!
No, you cannot use neither Gemini CLI nor Code Assist via Workspace — at least not at the moment. However, if you upgrade your Workspace plan, you can use Gemini Advanced via the Web or app interfaces.
Workspace (standard?) customer for over a decade.
In the case of Gemini CLI, it seems Google does not even support Workspace accounts in the free tier. If you want to use Gemini CLI as a Workspace customer, you must pay separately for it via API billing (pay-as-you-go). Otherwise, the alternative is to login with a personal (non-Workspace) account and use the free tier.
I was wondering what Gemini Advanced is. I don't see any mention of a Gemini Advanced here, but there is a Gemini Pro and a Gemini Ultra: https://gemini.google/subscriptions/
I had gotten the impression that Workspace might entitle us to some API credits or something based on section 3A here where they describe how to authenticate with the API via your Workspace account https://github.com/google-gemini/gemini-cli/blob/main/docs/cli/authentication.md . That document does explicitly mention "Gemini Code Assist for Workspace" but I think I saw another website from Google agreeing with you and saying you can't use it with a Workspace account currently.
Yeah, this is all a mess. Time to go back to bed for six months and just continue using whatever my corporate overlords have already handed to me
What does set Gemini via Workspace apart from other offerings like AI Studio is the nerfed output limit and safety filters. Also, I never got Gemini to ground replies in Google search, except when in Deep Research, or to execute code. Finally, Workspace users of Gemini either cannot keep their chat history, or have to keep the entire history for a predetermined period (deleting individual chats is not allowed).
(Update: Oh.. I'm only on business starter, I should be on business standard. need more business!)
Absolutely no offense but why do you (and a lot of people here) believe Google paid products gives you any privacy ?
I’m pretty sure even if they wanted to respect privacy of a subset of their users, they must have so much legacy code and data everywhere that they couldn’t even do it if they wanted to. And I’m not sure they’d want it anyway.
It's the second time I read this in this thread. May I ask why you think this is the case? And in which domains? I am very satisfied with 2.5 pro when it comes to philosophical/literary analysis, probably because of the super long context I can fill with whole books, and wanted to try Claude Code for the same purpose, but with folders, summaries, etc to make up for the shorter context length.
But also for text review on posts, etc.
Before Claude had the edge with agentic coding at least, but now even that is slipping.
You clearly have never had the "pleasure" to work with a Google product manager.
Especially the kind that were hired in the last 15-ish years.
This type of situation is absolutely typical, and probably one of the more benign thing among the general blight they typically inflict on Google's product offering.
The cartesian product of pricing options X models is an effing nightmare to navigate.
If I Could Talk to Satya...
I'd say:
“Hey Satya, love the Copilots—but maybe we need a Copilot for Copilots to help people figure out which one they need!”
Then I had them print out a table of Copilot plans:
- Microsoft Copilot Free - Github Copilot Free - Github Copilot Pro - Github Copilot Pro+ - Microsoft Copilot Pro (can only be purchased for personal accounts) - Microsoft 365 Copilot (can't be used with personal accounts and can only be purchased by an organization)
Copilot is stating the plans for its own services are confusing. Summarizing it as "regurgitation of an LLM" doesn't adequately capture the purpose of the post.
I like Gemini 2.5 Pro, too, and recently, I tried different AI products (including the Gemini Pro plan) because I wanted a good AI chat assistant for everyday use. But I also wanted to reduce my spending and have fewer subscriptions.
The Gemini Pro subscription is included with Google One, which is very convenient if you use Google Drive. But I already have an iCloud subscription tightly integrated with iOS, so switching to Drive and losing access to other iCloud functionality (like passwords) wasn’t in my plans.
Then there is the Gemini chat UI, which is light years behind the OpenAI ChatGPT client for macOS.
NotebookLM is good at summarizing documents, but the experience isn’t integrated with the Gemini chat, so it’s like constantly switching between Google products without a good integrated experience.
The result is that I end up paying a subscription to Raycast AI because the chat app is very well integrated with other Raycast functions, and I can try out models. I don’t get the latest model immediately, but it has an integrated experience with my workflow.
My point in this long description is that by being spread across many products, Google is losing on the UX side compared to OpenAI (for general tasks) or Anthropic (for coding). In just a few months, Google tried to catch up with v0 (Google Stitch), GH Copilot/Cursor (with that half-baked VSCode plugin), and now Claude Code. But all the attempts look like side-projects that will be killed soon.
It's not in Basic, Standard or Premium.
It's in a new tier called "Google AI Pro" which I think is worth inclusion in your catalogue of product confusion.
Oh wait, there's even more tiers that for some reason can't be paid for annually. Weird... why not? "Google AI Ultra" and some others just called Premium again but now include AI. 9 tiers, 5 called Premium, 2 with AI in the name but 6 that include Gemini. What a mess.
This is less about internal systems and more about either incompetence or active sabotage.
Tip: If you do annual billing for "Premium (5 TB)", you end up paying $21/month for 5TB of storage and the same AI features of "Google AI pro (2TB)"; which is only $1/month more than doing "Google AI Pro (2 TB)" (which only has monthly billing)
For me, it shows all the Gemini stuff in Premium, even the 5TB version.
https://web.archive.org/web/20250611035305/https://one.google.com/about/plans
I wonder what it will be next week.
I'm sure there is technically nothing that stopped you from treating this "Pay with Apple" thing as just another payment method inside the google account, except maybe additional complexity and red-tape.
Seen this many times when PMs, POs, and Devs code by features instead of trying to actually solve something. I don't even want to know what mess of a database schema is behind this monstrosity.
Apple is selling you a huge lucrative market.
Customers buy Apple’s curated marketplace.
Apple takes a cut for being in the middle and enabling all of this.
Believe me, I would never pay for most of the apps that I did pay for via Apple if it wasn’t via their marketplace and their consumer protections.
There is no counterfactual scenario where you and millions(!) of other ISVs get 100% of the same money without Apple.
What’s difficult to understand about these business relationships?
Enabling this like Ticketmaster enables selling tickets.
In ticketmaster's case I believe they give kickbacks and lucrative exclusive contracts with large venues, to squeeze smaller ones, maybe making whole tours use it but only kicking back to the biggest or select venues on the tour I think.
Apple sometimes does special deals and special rules with important providers, among many other tactics behind their moat. All single signons must also offer apple single sign-on, for instance, and they have even disabled access to customer accounts using their single sign-on for unrelated business disputes, though they walked it back in the big public example I'm aware of, the threat is there if you go against them in any way.
Ticketmaster is in no way comparable, because they gouge customers and provide no protections.
Someone in the music industry explained that both bands and venues like Ticketmaster because then Ticketmaster is the "bad guy" and the band can just shrug their shoulders and pretend to be the victim while profiting enormously from Ticketmaster's evil practices.
Okay, all the app developers pull out of iOS because they're not actually useful, in fact they should be paying Apple!
How many people do you think would still buy iPhones if there are 0 apps on the app store? Lmaooo, it's almost like it's a co-operative relationship and Apple don't deserve a huge cut because it's the apps that sell their phones.
I could see Stripe doing something like this. They protect the consumer and come down hard on the merchants.
Imagine them, and maybe a few other processors, competing for this business. The fee would probably drop below 30%. To a large degree, this is the sort of arrangement credit card processors already have between their merchants and consumers and that rate is single digit percentages. Not hard to imagine Visa or MasterCard running a SaaS transaction service for a 5-10% cut.
No way for you to scam me or make it hard ro cancel. I can view them all in the apple account subscription view.
No tricks, no unexpected behaviour.
You can't say a slave is free because their master is free to enslave them, and they're free to escape if they can. Sometimes you need rules to create real freedom.
Stripe already is a second place, non centralized, off platform.
I don't want to hunt down my predatory subscriptions in multiple places.
In the same vein: Games don’t cost less on the epic store despite their lower (compared to Steam) either, so as an end user it makes no difference where I buy games.
Maybe you like paying an extra 20%. That's your business. But fees like that affect the viability of lots of business ideas, including games. Having lower fees increases the pool of indie games.
30% is a robbery, and the confusion on the customer "ownership" is true, but it's not useful for the discussion to negate the advantage the _garden_ offers to the basic consumer
Unless you're trying to cancel the Apple ecosystem as a whole...
At least on my side, thats fine / intended. As long as their is no useable regulations around unsub dark patterns, that type of firewall is what I want as a customer.
Google is really bad at effective advertising.
But I found it to a little bit clunky and I guess I like the ui of google, I mean, the point is to get the point across. If you really hate the gemini ui, I am pretty sure that there is stylus extension which can beautify it or change the styles to your looking.
I guess I am an android user but still I understand your icloud subscription but if you're only choice as to why to not switch to google is passwords (but maybe you can mention more?), then for passwords, please try bitwarden, I found it to be really delightful.
I used 1Password in the past, and it’s possible to reconfigure most things to use another provider (passwords, app storage, etc.). AFAIK, you cannot reconfigure the full phone backup, which you must manually do without an iCloud storage quota. But why switch providers if I’m on the Apple ecosystem and the service is priced at the same price tiers? (I also use “Hide My Email” occasionally)
The only difference will be Gemini. However, my most significant percentage of AI usage is currently on desktops. The free tier of ChatGPT, Gemini, or Claude is okay for use on mobile.
The UI part that I mentioned is this: Gemini is just a web app, which means that if you need to use AI from the selected text or the app you are using, you need to copy and paste or capture a screenshot. But ChatGPT macOS integration is much better. It’s a native app that you can summon with a key combination, and it can automatically put the active app/text in context. I evaluated multiple options, and in the end, the winner for me was Raycast AI, because their app UX is incredible, and you can integrate your prompt with existing tools very easily. With prompts like: “For each item in the current selection, add a todo in @Apple Reminders”, or things like “Use @firecrawl to scrap the current page, then create a table with all the product prices and use @finder to store a CSV file”. You can save the prompt in a preset and use it as a Raycast command. That UX change was like night and day regarding daily AI usage. I chose to pay for the Raycast subscription, even if it was more expensive than switching everything from iCloud to Google and paying for only one service.
My point in the parent post is that today, Google is the company most well-positioned to be the absolute leader of the AI space. However, unlike OpenAI, they don’t seem to care much about the UX (at least outside Android), but if you use the assistant to work every day, the difference a good chat UX does is huge.
you can export and import the passwords and you can sync your photos to google photos
This is very confusing how they post about this on X, you would think you get additional usage. Messaging is very confusing.
I also have a pro subscription and wish I could get an API key with that with generous quota as well but pro is just for "consumers" using Gemini app I guess
I can't find any way to upgrade to a paid plan, is this even possible for individuals, or is it just "free or enterprise"?
/Edit: Okay I went through the Gemini docs. I found that in Google Cloud you can enable Gemini Code Assist Standard and Enterprise for the account
- Standard is $19.00/mo
- Enterprise is $45.00/mo
Difference between the 2 editions: https://cloud.google.com/products/gemini/pricing
/Edit2: Found the actual management screen: https://codeassist.google.com/overview
https://bun.sh/docs/bundler/executables
https://docs.deno.com/runtime/reference/cli/compile/
Note, I haven't checked that this actually works, although if it's straightforward Node code without any weird extensions it should work in Bun at least. I'd be curious to see how the exe size compares to Go and Rust!
Obviously everybody's requirements differ, but Node seems like a pretty reasonable platform for this.
If you have to run end point protection that will blast your CPU with load and it makes moving or even deleting that folder needlessly slow. It also makes the hosting burden of NPM (nusers) who must all install dependencies instead of (nCI instances), which isn't very nice to our hosts. Dealing with that once during your build phase and then packaging that mess up is the nicer way to go about distributing things depending on NPM to end users.
I guess it needs to start various processes for the MCP servers and whatnot? Just spawning another Node is the easy way to do that, but a bit annoying, yeah.
Claude also requires npm, FWIW.
I've forgotten how to count that low.
It's the only argument I can think of, something like Go would be goated for this use case in principle.
Re-running `cargo install <crate>` will do that. Or install `cargo-update`, then you can bulk update everything.
And it works hella better than using pip in a global python install (you really want pipx/uvx if you're installing python utilities globally).
IIRC you can install Go stuff with `go install`, dunno if you can update via that tho.
A single, pre-compiled binary is convenient for the user's first install only.
(Aside from the fact that allowing "use pip" completely defeats the purpose of any other of these mechanisms, so it's a poster-child example of security-theater)
Reasoning: it’s a Python tool, therefore it shouldn’t require anything (any 3rd party package manager) beyond Python.
Its not.
Its convenient for CIs, for deployment, for packaging, for running multiple versions. It's extremely simple to update (just replace the binary with another one).
Now, e.g. "just replacing one file with another" may not have convenience commands like "npm update". But its not hard.
My point is that a pre-compiled binary is extremely more convenient for *everyone involved in the delivery pipeline* including the end-user. Especially for delivering updates.
As someone who's packaged Javascript(node), Ruby, Go and rust tools in .debs, snap, rpms: packaging against a dynamic runtime (node, ruby, rvm etc) is a giant PIAS that will break on a significant amount of users' machines, and will probably break on everyones machine at some point. Whereas packaging that binary is as simple as it can get: most such packages need only one dependency that everyone and his dog already has: libc.
The easiest is running "sudo apt update && sudo apt upgrade" and have my whole system updated. Instead of writing some script to get it done from some github's releases page and hoping that it's not hijacked.
Having a sensible project is what make it easy down the line (including not depending on gnu libc if not needed as some people uses musl). And I believe it's easy to setup a repository if your code is proprietary (Just need to support the most likely distribution, like ubuntu, fedora, suse's tumbleweed,...)
How many developers have npm installed vs cargo? Many won't even know what cargo is.
Just `wget -O ~/.local/bin/gemini-cli https://ci.example.com/assets/latest/gemini-cli` (Or the CURL version thereof) It can pick the file off github, some CI's assets, a package repo, a simple FTP server, an HTTP fileserver, over SSH, from a local cache, etc. It's so simple that one doesn't need a package manager. So there commonly is no package manager.
Yet in this tread people are complaining that "a single binary" is hard to manage/update/install because there's no package manager to do that with. It's not there, because the manage/update/install is so simple, that you don't need a package manager!
You might not know the reason ppl use package managers. Installing this "simple" way make it quite difficult to update and remove compared to using package managers. And although they are also "simple", it's quite a mess to manage packages manually in place of using such battle-tested systems
People use package managers for the following:
- to manage dependencies - to update stuff to a specific version or the latest version - to downgrade stuff - to install stuff - to remove stuff
any of these, except for the dependency management, are a single command, or easy to do manually, with a single compiled binary. They are so simple that they can easily be built into the tool. Or handled by your OSs package manager. Or with a "shell script" that the vendor can provide (instead of, or next to, the precompiled binary.
I did not say manually, you infer that. But I never meant that. The contrary: because it's so simple, automating that, or have your distro, OS or package manager do this for you, is trivial. As opposed to that awful "curl example.com/install.sh | sudo tee -" or those horrible built-in updaters (that always start nagging when I open the app - the one moment that I don't want to be bothered by updates because I need the app now)
The only reason one would then need a package manager is to manage dependencies. But a precompiled binary like Go's or Rusts typically are statically compiled so they have no (or at most one) dependency.
Imagine the ease of a single ".targz" or so that includes the correct python version, all pips, all ENV vars, config files, and is executable. If you distribute that - what do you still need pip for? If you distribute that, how simple would turning it into a .deb, snap, dmg, flatpack, appimg, brew package, etc be? (Answer: a lot easier than doing this for the "directory of .py files. A LOT)
pip is there so you don't need to do that. In the deployment world, you really want one version per system for everything and know that everything is in sync. To get that the solution was a distribution of software and a tool to manage them. We then extended that to programming language ecosystem and pip is part of the result.
But for workstation, a lot of people wants the latest, so the next solution was to be able to abstract the programming language ecosystem from the distribution (And you may not have a choice in the case of macOS), so what we get is directory-restricted interactions (go, npm,..) or doing shell magic so that the tooling think it's the system (virtual env,...).
It's a neat trick, but the only reason to do so is if you want to distribute compiled version of a software to customer. But if the user have access to the code, It's better to adapt the software to the system (repositories, flatpak...) or build a system around it (VM, containers, ...).
Also, react-reconciler caught my eye. Apparently that's a dependency of ink, which lets you write text-based UIs in React.
That and opentelemetry, whatever the heck that is
uv self update
yt-dlp --update
Anthropic's Claude Code is also installed using npm/npx.
My exact same reaction when I read the install notes.
Even python would have been better.
Having to install that Javascript cancer on my laptop just to be able to try this, is a huge no.
Btw, the largest deps in this are React and Open Telemetry.
I really don't mind either way. My extremely limited experience with Node indicates they have installation, packaging and isolation polished very well.
https://www.npmjs.com/package/pkg
or perhaps this one:
Again, I haven't used aider in a while so perhaps that's not the case.
For complicated changes Aider is much more likely to stop and need help, whereas Claude Code will just go and go and end up with something.
Whether that's worth the different economic model is up to you and your style and what you're working on.
Appreciate all the takes so far, the team is reading this thread for feedback. Feel free to pile on with bugs or feature requests we'll all be reading.
currently it seems these are the CLI tools available. Is it possible to extend or actually disable some of these tools (for various reasons)?
> Available Gemini CLI tools:
- ReadFolder
- ReadFile
- SearchText
- FindFiles
- Edit
- WriteFile
- WebFetch
- ReadManyFiles
- Shell
- Save Memory
- GoogleSearch Says hello, and just returns right away.
gemini "Say hello"
Fails as it doesn't take any arguments.
{ "excludeTools": ["run_shell_command", "write_file"] }
but if you ask Gemini CLI to do this it'll guide you!
You can also extend with the Extensions feature - https://github.com/google-gemini/gemini-cli/blob/main/docs/extension.md
At the very least, we need better documentation on how to get that environment variable, as we are not on GCP and this is not immediately obvious how to do so. At the worst, it means that your users paying for gemini don't have access to this where your general google users do.
Also this doco says GOOGLE_CLOUD_PROJECT_ID but the actual tool wants GOOGLE_CLOUD_PROJECT
[^1]: https://console.cloud.google.com/marketplace/product/google/cloudaicompanion.googleapis.com
Workspace users [edit: cperry was wrong] can get the free tier as well, just choose "More" and "Google for Work" in the login flow.
It has been a struggle to get a simple flow that works for all users, happy to hear suggestions!
Just a heads-up: your docs about authentication on Github say to place a GOOGLE_CLOUD_PROJECT_ID as an environment variable. However, what the Gemini CLI is actually looking for, from what I can tell, is a GOOGLE_CLOUD_PROJECT environment variable with the name of a project (rather than its ID). You might want to fix that discrepancy between code and docs, because it might confuse other users as well.
I don’t know what constraints made you all require a project ID or name to use the Gemini CLI with Workspace accounts. However, it would be far easier if this requirement were eliminated.
noted on documentation, there's a PR in flight on this. also found some confusion around gmail users who are part of the developer program hitting issues.
Well, I've just set up Gemini CLI with a Workspace account project in the free tier, and it works apparently for free. Can you explain whether billing for that has simply not been configured yet, or where exactly billing details can be found?
For reference, I've been using this panel to keep track of my usage in the free tier of the Gemini API, and it has not been counting Gemini CLI usage thus far: https://console.cloud.google.com/apis/api/generativelanguage.googleapis.com/quotas
Unfortunately all of that is pretty confusing, so I'll hold off using Gemini CLI until everything has been clarified.
Maybe you have access to an AI solution for this.
* First google forced me to start paying for my email domain.
* Then they increased the cost to force me to pay for AI features
* Now, I can't actually use the AI features without spending even more money, I could use them if I just had a gmail address and didn't pay google.
Well done Google, you've finally pursaded me to get around to transfering my custom email domain off google. Anyone have any preferences?
Do you mean that they stopped offering the legacy free tier and you had to upgrade to a paid plan? If that's the case, they reverted their decision and it was possible to go back to the free tier. I don't know if it is still possible, as this was 3 years ago, but here's a thread outlining how to do it. https://www.reddit.com/r/gsuitelegacymigration/comments/urkyj2/if_you_have_already_upgraded_to_a_paid_account/
When I heard about it (about 6 weeks after that post), I applied to go back to free, but was told I was too late.
1. CodeRunner - https://github.com/BandarLabs/coderunner/tree/main?tab=readme-ov-file#option-3-gemini-cli
like to just get a short response - for simple things like "what's a nm and grep command to find this symbol in these 3 folders". I use gemini alot for this type of thing already
Or would that have to be a custom prompt I write?
other people use simon willison's `llm` tool https://github.com/simonw/llm
Both allow you to switch between models, send short prompts from a CLI, optionally attach some context. I prefer mods because it's an easier install and I never need to worry about Python envs and other insanity.
There's also wrappers that place the command directly in your terminal prompt if you run shelp-c
All different products doing the sameish thing. I don’t know where to send users to do anything. They are all licensed differently. Bonkers town.
Many of these are not even remotely similar.
So Vertex is like AWS Bedrock for GCP?
And not that there isn’t a level of knowledge you can gain to answer these questions, it’s just not clear.
Edit: I should mention that I'm accessing this through Gemini Code Assist, so this may be something out of your wheelhouse.
I don't think that's capacity, you should see error codes.
> You exceeded your current quota, please check your plan and billing details. For more information on this error, head to: https://ai.google.dev/gemini-api/docs/rate-limits.
Discouraging
[API Error: {"error":{"message":"{\n \"error\": {\n \"code\": 429,\n \"message\": \"Resource has been exhausted (e.g. check quota).\",\n
\"status\": \"RESOURCE_EXHAUSTED\"\n }\n}\n","code":429,"status":"Too Many Requests"}}]
Please wait and try again later. To increase your limits, request a quota increase through AI Studio, or switch to another /auth method
I'm a Gemini Pro subscriber and I would love to be able to use my web-based chat resource limits with, or in addition to, what is offered here. I have plenty of scripts that are essentially "Weave together a complex prompt I can send to Gemini Flash to instantly get the answer I'm looking for and xclip it to my clipboard", and this would finally let me close the last step in that scripts.
Love what I'm seeing so far!
Is the recommendation to specifically ask "analyze the codebase" here?
- On a new chat I have to re-approve things like executing "go mod tidy", "git", write files... I need to create a new chat for each feature, (maybe an option to clear the current chat on VsCode would work)
- I have found some problems with adding some new endpoint on an example Go REST server I was trying it on, it just deleted existing endpoints on the file. Same with tests, it deleted existing tests when asking to add a test. For comparison I didn't find these problems when evaluating Amp (uses Claude 4)
Overall it works well and hope you continue with polishing it, good job!!
And thinking is stupid. "Show me how to generate a random number in python"... 15s later you get an answer.
I had a somehos similar problem with Claude 3.7, where I had a class named "Workflow" and it got nuts, producing code/comments I didn't ask for, all related to some "workflow" that it tried to replicate and not my code, it was strange.
A natural question to ask is, if in the near future, can Google One "Google AI Pro" subscribers have higher limits than what is offered for free users?
CC has this issue too, but way less often, and second shot almost always works.
- Here [1] it says "Project settings override user settings." How does gemini determine if we're in a project? Does it look for a `.gemini` folder in the current working directory as well as every parent directory up to the root? Would Gemini be able to read the contents of a subfolder of the CWD if the subfolder contains a different `.gemini` folder?
- I don't see documentation for the `selectedAuthType` field in the documentation for settings.json. Mine says `oauth-personal`. I could've sworn I signed in with my Google Workspace account. Does `oauth-personal` apply to Workspace accounts?
And a feature request: it would be nice to add a restriction in the settings.json file forcing anybody who uses gemini in that project to sign in to a Workspace account in a specific org (or use a specific project, I guess).
High ROI feature requests:
• Pattern-based permissions - Bash(git:) to allow git but not rm, Write(logs/.txt) for path scoping
• CLI permission flags - --allowedTools "Read,Bash(npm test)" --deniedTools "Write" for session overrides
• Allow/deny precedence rules - explicit deny should override general allow (security principle)
• Config file hierarchy - system → user → project precedence for policy enforcement
Medium ROI improvements:
• Command argument filtering - whitelist git commit but not git --exec-path=/bin/sh
• Multiple config formats - support both simple arrays and structured permission objects
• Runtime permission diagnostics - gemini permissions list to debug what's actually enabled
• Environment variable injection - top-level env config for OTEL endpoints, API keys, etc.
The permission engine is really the key piece - once you can express "allow X but not Y within X", it unlocks most advanced use cases. Keep up the great work!
Use Jules, also by Google if you need what you describe.
Even with 1M context, for large projects, it makes sense to define boundaries These will typically be present in some form, but they are not available precisely to the coding agent. Imagine there was a simple YAML format where I could specify modules and where they can be found in the source tree, and the APIs of other modules it interacts with. Then it would be trivial to turn this into a context that would very often fit into 1M tokens. When an agent decides something needs to be done in the context of a specific module, it could then create a new context window containing exactly that module, effetively turning a large codebase into a small codebase, for which Gemini is extraordinarily effective.
I wonder if it is a concious decision not to include this (I imagine it opens a lot of possibilities of going crazy, but it also seems to be the source of a great amount of Claud Code's power). I would very much like to play with this if it appears in gemini-cli
Next step would be the possibility to define custom prompts, toolsets and contexts for specific re-occuring tasks, and these appearing as tools to the main agent. Example for such a thing: create_new_page. The prompt could describe the steps one needs to create the page. Then the main agent could simply delegate this as a well-defined task, without cluttering its own context with the operational details.
https://github.com/google-gemini/gemini-cli/blob/main/docs/cli/index.md#non-interactive-mode
But it is still worth a try and may be possible with some prompting and duct tape.
Edit: I tried it. The setup was a breeze. I fed the CLI two git commit IDs and some light prompting on what to look for. It gave a reasonable response. I'll try on a real PR shortly.
I think with better prompting on my end, as I have good experience with Gemini, this will be awesome. You probably could tweak a lot on your end as well, don't let it get stuck in cycles.
- Open-source (Apache 2.0, same as OpenAI Codex)
- 1M token context window
- Free tier: 60 requests per minute and 1,000 requests per day (requires Google account authentication)
- Higher limits via Gemini API or Vertex AI
- Google Search grounding support
- Plugin and script support (MCP servers)
- Gemini.md file for memory instruction
- VS Code integration (Gemini Code Assist)
We are now three years into the AI revolution and they are still forcing us to copy and paste and click click crazy to get the damn files out.
STOP innovating. STOP the features.
Form a team of 500 of your best developers. Allocate a year and a billion dollar budget.
Get all those Ai super scientists into the job.
See if you can work out “download all files”. A problem on the scale of AGI or Dark Matter, but one day google or OpenAI will crack the problem.
When you hop over to platforms that use the API, the files get written/edited in situ. No copy/pasting. No hunting for where to insert edited code.
Trust me it's a total game changer to switch. I spent so much time copy/pasting before moving over.
Is your vision with Gemini CLI to be geared only towards non-commercial users? I have had a workspace account since GSuite and have been constantly punished for it by Google offerings all I wanted was gmail with a custom domain and I've lost all my youtube data, all my fitbit data, I cant select different versions of some of your subscriptions (seemingly completely random across your services from a end-user perspective), and now as a Workspace account I cant use Gemini CLI for my work, which is software development. This approach strikes me as actively hostile towards your loyal paying users...
... and other stuff.
Googlers, we should not have to do all of this setup and prep work for a single account. Enterprise I get, but for a single user? This is insufferable.
Have you managed to overcome that?
No mention of accessibility in https://github.com/google-gemini/gemini-cli/blob/0915bf7d677504c28b079693a0fe1c853adc456e/docs/cli/configuration.md either
... it's a big deal because the only way to really make sense of using LLMs in any context is to have good observability data you can analyze later. And so the traces that they emit here will show all the CLI invocations, inputs/outputs and context for each chat turn in a session, and you can look for patterns that exhibit good or bad stuff.
It integrates with VS Code, which suits my workflow better. And buying credits through them (at cost) means I can use any model I want without juggling top-ups across several different billing profiles.
If it sounds too good to be true, it probably is. What’s the catch? How/why is this free?
Also they can throttle the service whenever they feel it's too costly.
This is shown at the top of the screen in https://aistudio.google.com/apikey as the suggested quick start for testing your API key out.
Not a great look. I let our GCloud TAM know. But still.
Set up not too long ago, and afaik pretty load-bearing for this. Feels great, just don’t ask me any product-level questions. I’m not part of the Gemini CLI team, so I’ll try to keep my mouth shut.
Not going to lie, I’m pretty anxious this will fall over as traffic keeps climbing up and up.
It's interesting to see how one team / product gets rebranded to another in Google.
Because it says in the README:
> Authenticate: When prompted, sign in with your personal Google account. This will grant you up to 60 model requests per minute and 1,000 model requests per day using Gemini 2.5 Pro.
> For advanced use or increased limits: If you need to use a specific model or require a higher request capacity, you can use an API key: ...
When I have the Google AI Pro subscription in my Google account, and I use the personal Google account for authentication here, will I also have more requests per day then?
I'm currently wondering what makes more sense for me (not for CLI in particular, but for Gemini in general): To use the Google AI Pro subscription, or to use an API key. But I would also want to use the API maybe at some point. I thought the API requires an API key, but here it seems also the normal Google account can be used?
We really are living in the future
I haven't looked at this Gemini CLI thing yet, but if its open source it seems like any model can be plugged in here?
I can see a pathway where LLMs are commodities. Every big tech company right now both wants their LLM to be the winner and the others to die, but they also really, really would prefer a commodity world to one where a competitor is the winner.
If the future use looks more like CLI agents, I'm not sure how some fancy UI wrapper is going to result in a winner take all. OpenAI is winning right now with user count by pure brand name with ChatGPT, but ChatGPT clearly is an inferior UI for real work.
But in many other niches (say embedded), the workflow is different. You add a feature, you get weird readings. You start modelling in your head, how the timing would work, doing some combination of tracing and breakpoints to narrow down your hypotheses, then try them out, and figure out what works the best. I can't see the CLI agents do that kind of work. Depends too much on the hunch.
Sort of like autonomous driving: most highway driving is extremely repetitive and easy to automate, so it got automated. But going on a mountain road in heavy rain, while using your judgment to back off when other drivers start doing dangerous stuff, is still purely up to humans.
Im actually interested to see if we see a rise in demand for DRAM that is greater than usual because more software is vibe coded than being not, or some form of vibe coding.
If the module just can't be documented in this way in under 100 lines, it's a good time to refactor. Chances are if Claude's context window is not enough to work with a particular module, a human dev can't either. It's all about pointing your LLM precisely at the context that matters.
I’ve been using Claude for a side project for the past few weeks and I find that we really get into a groove planning or debugging something and then by the time we are ready to implement, we’ve run out of context window space. Despite my best efforts to write good /compact instructions, when it’s ready to roll again some of the nuance is lost and the implementation suffers.
I’m looking forward to testing if that’s solved by the larger Gemini context window.
Approaching the context window limit in Claude Code, having it start to make more and worse mistakes, then seeing it try to compact the context and keep going, is a major "if you find yourself in a hole, stop digging" situation.
I'm trying to get better at the /resume and memories to try and get more value out of the tool.
As for /compact, if I’m nearing the end of my context window (around 15%) and are still in the middle of something, I’ll give /compact very specific details about how and what to compact. Let’s say we are debugging an error - I might write something along the lines of “This session is about to close and we will continue debugging in next session. We will be debugging this error message [error message…]. Outline everything we’ve tried that didn’t work, make suggestions about what to try next, and outline any architecture or files that will be critical for this work. Everything else from earlier on in this session can be ignored.” I’ve had decent success with that. More so on debugging than trying to hand off all the details of a feature that’s being implemented.
Reminder: you need context space for compact, so leave a little head room.
If you see that 20% remaining warning, something has gone badly wrong and results will probably not get better until you clear the context and start again.
>This project leverages the Gemini APIs to provide AI capabilities. For details on the terms of service governing the Gemini API, please refer to the terms for the access mechanism you are using:
Click Gemini API, scroll
>When you use Unpaid Services, including, for example, Google AI Studio and the unpaid quota on Gemini API, Google uses the content you submit to the Services and any generated responses to provide, improve, and develop Google products and services and machine learning technologies, including Google's enterprise features, products, and services, consistent with our Privacy Policy.
>To help with quality and improve our products, human reviewers may read, annotate, and process your API input and output. Google takes steps to protect your privacy as part of this process. This includes disconnecting this data from your Google Account, API key, and Cloud project before reviewers see or annotate it. Do not submit sensitive, confidential, or personal information to the Unpaid Services.
If you pay for API: No
At the bottom of README.md, they state:
"This project leverages the Gemini APIs to provide AI capabilities. For details on the terms of service governing the Gemini API, please refer to the terms for the access mechanism you are using:
* Gemini API key
* Gemini Code Assist
* Vertex AI"
The Gemini API terms state: "for Unpaid Services, all content and responses is retained, subject to human review, and used for training".
The Gemini Code Assist terms trifurcate for individuals, Standard / Enterprise, and Cloud Code (presumably not relevant).
* For individuals: "When you use Gemini Code Assist for individuals, Google collects your prompts, related code, generated output, code edits, related feature usage information, and your feedback to provide, improve, and develop Google products and services and machine learning technologies."
* For Standard and Enterprise: "To help protect the privacy of your data, Gemini Code Assist Standard and Enterprise conform to Google's privacy commitment with generative AI technologies. This commitment includes items such as the following: Google doesn't use your data to train our models without your permission."
The Vertex AI terms state "Google will not use Customer Data to train or fine-tune any AI/ML models without Customer's prior permission or instruction."
What a confusing array of offerings and terms! I am left without certainty as to the answer to my original question. When using the free version by signing in with a personal Google account, which doesn't require a Gemini API key and isn't Gemini Code Assist or Vertex AI, it's not clear which access mechanism I am using or which terms apply.
It's also disappointing "Google's privacy commitment with generative AI technologies" which promises that "Google doesn't use your data to train our models without your permission" doesn't seem to apply to individuals.
A bit gutted by the `make sure it is not a workspace account`. What's wrong with Google prioritising free accounts vs paid accounts? This is not the first time they have done it when announcing Gemini, too.
I do not get it why they don’t pick Go or Rust so i get a binary.
This perfectly demonstrates the benefit of the nodejs platform. Trivial to install and use. Almost no dependency issues (just "> some years old version of nodejs"). Immediately works effortlessly.
I've never developed anything on node, but I have it installed because so many hugely valuable tools use it. It has always been absolutely effortless and just all benefit.
And what a shift from most Google projects that are usually a mammoth mountain of fragile dependencies.
(uv kind of brings this to python via uvx)
npm install -g @google/gemini-cli
Piping a downloaded shell script to bash seems pretty much the same effort.
It would be much better if I didn’t have to reinstall it every time I change Node versions.
Gemini Pro and Claude play off of each other really well.
Just started playing with Gemini CLI and one thing I miss immediately from Claude code is being able to write and interject as the AI does its work. Sometimes I interject by just saying stop, it stops and waits for more context or input or ai add something I forgot and it picks it up..
When you use Gemini Code Assist for individuals, Google collects your prompts, related code, generated output, code edits, related feature usage information, and your feedback to provide, improve, and develop Google products and services and machine learning technologies.
To help with quality and improve our products (such as generative machine-learning models), human reviewers may read, annotate, and process the data collected above. We take steps to protect your privacy as part of this process. This includes disconnecting the data from your Google Account before reviewers see or annotate it, and storing those disconnected copies for up to 18 months. Please don't submit confidential information or any data you wouldn't want a reviewer to see or Google to use to improve our products, services, and machine-learning technologies.
Even senior programmers can misuse tools, happens to all of us. LLMs sucks at software design, choosing algorithms and are extremely crap unless you exactly tell them what to do and what not to do. I leave the designing to myself, and just use OpenAI and local models for implementation, and with proper system prompting you can get OK code.
But you need to build up a base-prompt you can reuse, by basically describing what is good code for you, as it differs quite a bit from person to person. This is what I've been using as a base for agent use: https://gist.github.com/victorb/1fe62fe7b80a64fc5b446f82d3137398, but need adjustments depending on the specific use case
Although I've tried to steer Google's models in a similar way, most of them are still overly verbose and edit-happy, not sure if it's some Google practice that leaked through or something. Other models are way easier to stop from outputting so much superfluous code, and overall following system prompts.
wget https://cosmo.zip/pub/cosmos/bin/python -qO python.com
chmod +x python.com
./python.com
./python.com -m pip download Click
mkdir -p Lib && cd Lib
unzip ../click*.whl
cd ..
zip -qr ./python.com Lib/
./python.com # can now import click
If this is legal, it shouldn’t be.
"If you don't want this data used to improve Google's machine learning models, you can opt out by following the steps in Set up Gemini Code Assist for individuals."
and then the link: https://developers.google.com/gemini-code-assist/docs/set-up-gemini#read-privacy-notice
If you pay for code assist, no data is used to improve. If you use a Gemini API key on a pay as you go account instead, it doesn't get used to improve. It's just if you're using a non-paid, consumer account and you didn't opt out.
That seems different than what you described.
"You can find the Gemini Code Assist for individuals privacy notice and settings in two ways:
- VS Code - IntelliJ "
I guess the key question is whether the Gemini CLI, when used with a personal Google account, is governed by the broader Gemini Apps privacy settings here? https://myactivity.google.com/product/gemini?pli=1
If so, it appears it can be turned off. However, my CLI activity isn't showing up there?
Can someone from Google clarify?
When you look at the github repo for the gemini CLI:
https://github.com/google-gemini/gemini-cli/tree/main
At the bottom it specifies that the terms of service are dependent on the underlying mechanism that the user chooses to use to fulfill the requests. You can use code assist, gemini API, or Vertex AI. My layperson's perspective is that it's positioned as a wrapper around another service, whose terms you already have accepted/enabled. I would imagine that is separate from the Gemini app, the settings for which you linked to.
Looking at my own settings, my searches on the gemini app appear, but none of my gemini API queries appear.
However, as others pointed out, that link take you to here: https://developers.google.com/gemini-code-assist/resources/privacy-notice-gemini-code-assist-individuals Which, at the bottom says: "If you don't want this data used to improve Google's machine learning models, you can opt out by following the steps in Set up Gemini Code Assist for individuals." and links to https://developers.google.com/gemini-code-assist/docs/set-up-gemini#read-privacy-notice. That page says "You'll also see a link to the Gemini Code Assist for individuals privacy notice and privacy settings. This link opens a page where you can choose to opt out of allowing Google to use your data to develop and improve Google's machine learning models. These privacy settings are stored at the IDE level."
The issue is that there is no IDE, this is the CLI and no such menu options exist.
Are you saying the Gemini Apps Activity switch controls? Or, that if I download VS Code or Intelli J and make the change, it applies to the CLI? https://developers.google.com/gemini-code-assist/docs/set-up-gemini#read-privacy-notice says "These privacy settings are stored at the IDE level."
https://github.com/google-gemini/gemini-cli/tree/main
If you scroll to the bottom, it says that the terms of service are governed based on the mechanism by which you access Gemini. If you access via code assist (which the OP posted), you abide by those privacy terms of code assist, one of the ways of which you access is VScode. If you access via the Gemini API, then those terms apply.
So the gemini CLI (as I understand it) doesn't have their own privacy terms, because it's an open source shell on top of another Gemini system, which could have one of a few different privacy policies based on how you choose to use it and your account settings.
(Note: I work for google, but not on this, this is just my plain reading of the documentation)
This depends entirely on the type of auth method you use.
Auth method 1: Yes. When you use your personal Google account, the Gemini Code Assist Privacy Notice for Individuals applies. Under this notice, your prompts, answers, and related code are collected and may be used to improve Google's products, which includes model training."
Off-topic, but I wish this kind of plain language doc existed for Google One vs Google Workspace as well.
It's even more nuanced than that.
Google recently testified in court that they still train on user data after users opt out from training [1]. The loophole is that the opt-out only applies to one organization within Google, but other organizations are still free to train on the data. They may or may not have cleaned up their act given that they're under active investigation, but their recent actions haven't exactly earned them the benefit of the doubt on this topic.
https://support.google.com/accounts/answer/10549751
That said, once your data is inside an LLM, you can't really unscramble the omelette.
We need open infrastructure and models.
They get a ton of tax incentives, subsidies, etc to build shoddy infrastructure that can only be used for big box stores (pretty much), so the end cost for Walmart to build their stores is quite low.
They promise to employ lots of locals, but many of those jobs are intentionally paid so low that they're not actually living wages and employees are intentionally driven to government help (food stamps, etc), and together with other various tax cuts, etc, there's a chance that even their labor costs are basically at break even.
Integrated local stores are better for pretty much everything except having a huge mass to throw around and bully, bribe (pardon me, lobby) and fool (aka persuade aka PR/marketing).
There is a reason why rural communities welcome Wal-Mart with open arms. Not such a big deal now that you can mail-order anything more-or-less instantly, but back in the 80s when I was growing up in BFE, Wal-Mart was a godsend.
The latter wasn't what most people think of as a Sears store, because the local economy could never have supported such a thing. It was more like a small office with a counter and a stockroom behind it. They didn't keep any inventory, but could order products for pickup in about a week. Pickup, mind you. You still had to drive to town to get your order. As stupid as this sounds, it was 10x worse in person.
So if Wal-Mart didn't exist, it would have had to be invented. It was not (just) a monster that victimized smaller merchants and suppliers, a tax scam, or a plot to exploit the welfare system. It was something that needed to happen, a large gap in the market that eventually got filled.
Nowadays I wouldn't set foot in one, but it was different at the time. I didn't mean to write a long essay stanning for Wal-Mart, but your original post is a bit of a pet peeve.
Also, did you read my original comment and miss the part about Walmart and co being predatory businesses? That's why they can keep those prices so low, because they're socializing their costs to everyone else.
It may have shifted where people buy things they can wait for, but for weekly shopping I don’t think it has.
Walmart spread so successfully precisely because so many people immediately started shopping there for all of the basics.
If the data is sent by a user to sub-unit X of Google, and X promised not to use it for training, it implies that X can share this data with sub-unit Y only if Y also commits not to use the data for training. Breaking this rule would get everyone in huge trouble.
OTOH, when sub-unit X said "We promise not to use data from the public website if the website owner asks us not to", it does not imply another sub-unit Y must follow that commitment.
Well... you are sending your data to a remote location that is not yours.
EDIT: Lmao, case in point, two sibling comments pointing out that Google does indeed do this anyway via some loophole; also they can just retain the data and change the policy unilaterally in the future.
If you want privacy do it local with Free software.
Which pretty much means if you are using it for free, they are using your data.
I don't see what is alarming about this, everyone else has either the same policy or no free usage. Hell the surprising this is that they still let free users opt-out...
That’s not true. ChatGPT, even in the free tier, allows users to opt out of data sharing.
Not if you pay for it.
Not if you pay for it.
Today.
In six months, a "Terms of Service Update" e-mail will go out to an address that is not monitored by anyone.
There's also zero chance they will risk paying customers by changing this policy.
This is just how things are these days. The track record of Google, and most of the rest of the industry, does not inspire confidence.
The resulting class-action lawsuit would bankrupt the company, along with the reputation damage, and fines.
It doesn't look like they care at all about the law though
The judge, Alsup J, ruled that this was lawful.
So they cared at least a bit, enough to spend a lot of money buying books. But they didn't care enough not to acquire online libraries held apparently without proper licensing.
>Alsup wrote that Anthropic preferred to "steal" books to "avoid 'legal/practice/business slog,' as cofounder and CEO Dario Amodei put it."
Aside: using the term steal for copyright infringement is a particularly egregious misuse for a judge who should know that stealing requires denying others of the use of the stolen articles; something which copyright infringement via an online text repository simple could not do.
If this is due to compliance with law I wonder how they can make the zero-data-retention agreement work... The companies I've seen have this have not mention that they themself retain the data...
* The first section states "Privacy Notice: The collection and use of your data are described in the Gemini Code Assist Privacy Notice for Individuals." That in turn states "If you don't want this data used to improve Google's machine learning models, you can opt out by following the steps in Set up Gemini Code Assist for individuals.". That page says to use the VS Code Extension to change some toggle, but I don't have that extension. It states the extension will open "a page where you can choose to opt out of allowing Google to use your data to develop and improve Google's machine learning models." I can't find this page.
* Then later we have this FAQ: "1. Is my code, including prompts and answers, used to train Google's models? This depends entirely on the type of auth method you use. Auth method 1: Yes. When you use your personal Google account, the Gemini Code Assist Privacy Notice for Individuals applies. Under this notice, your prompts, answers, and related code are collected and may be used to improve Google's products, which includes model training." This implies Login with Google users have no way to opt out of having their code used to train Google's models.
* But then in the final section we have: "The "Usage Statistics" setting is the single control for all optional data collection in the Gemini CLI. The data it collects depends on your account type: Auth method 1: When enabled, this setting allows Google to collect both anonymous telemetry (like commands run and performance metrics) and your prompts and answers for model improvement." This implies prompts and answers for model improvement are considered part of "Usage Statistics", and that "You can disable Usage Statistics for any account type by following the instructions in the Usage Statistics Configuration documentation."
So these three sections appear contradictory, and I'm left puzzled and confused. It's a poor experience compared to competitors like GitHub Copilot, which make opting out of model training simple and easy via a simple checkbox in the GitHub Settings page - or Claude Code, where Anthropic has a policy that code will never be used for training unless the user specifically opts in, e.g. via the reporting mechanism.
I'm sure it's a great product - but this is, for me, a major barrier to adoption for anything serious.
*What we DON'T collect:*
- *Personally Identifiable Information (PII):* We do not collect any personal information, such as your name, email address, or API keys.
- *Prompt and Response Content:* We do not log the content of your prompts or the responses from the Gemini model.
- *File Content:* We do not log the content of any files that are read or written by the CLI.
I still have yet to replace a single application with an LLM, except for (ironically?) Google search.
I still use all the same applications as part of my dev work/stack as I did in the early 2020's. The only difference is occasionally using an LLM baked into to one of them but the reality is I don't do that much.
I hope this is something they're working on making clearer.
If I were you I'd assume they're using all of it for everything forever and act accordingly.
The newer models are quantized and distilled (I confirmed this with someone who works on the team), and are a significantly worse experience. I prefer OpenAI O3 and o4-mini models to Gemini 2.5 Pro for general knowledge tasks, and Sonnet 4 for coding.
I haven't tried Gemini since the latest updates, but earlier ones seemed on par with opus.
To clear everything up, we've put together a single doc that breaks down the Terms of Service and data policies for each account type, including an FAQ that covers the questions from this thread.
Here’s the link: https://github.com/google-gemini/gemini-cli/blob/main/docs/tos-privacy.md
Thanks again for pushing for clarity on this!
### 1. Is my code, including prompts and answers, used to train Google's models?
This depends entirely on the type of auth method you use.
- *Auth method 1:* Yes. When you use your personal Google account, the Gemini Code Assist Privacy Notice for Individuals applies. Under this notice, your *prompts, answers, and related code are collected* and may be used to improve Google's products, which includes model training.
### 2. What are "Usage Statistics" and what does the opt-out control?
The "Usage Statistics" setting is the single control for all optional data collection in the Gemini CLI. The data it collects depends on your account type:
- *Auth method 1:* When enabled, this setting allows Google to collect both anonymous telemetry (like commands run and performance metrics) and *your prompts and answers* for model improvement.
Does this mean that for a personal account, your data is always "collected", but the opt out may prevent your data from being used for training? Also, the question was about "code", but this addresses only addresses "prompts and answers". Is code covered under prompts? The first FAQ lists "*prompts, answers, and related code are collected*" as separate items so it's still not clear what happens to code and if there's a way to opt out from your code being used for model training IMO.
that's a read flag. That's a weasel word in my opinion. If we took Google to court, you can easily say "statistics" does not include user's code.
From an initial parse of your linked tos-privacy.md doc, it seems like the answer is "no" -- but that seems bonkers to me, so I hope I'm misreading or misunderstanding something!
However, Gemini at one point output what will probably be the highlight of my day:
"I have made a complete mess of the code. I will now revert all changes I have made to the codebase and start over."
What great self-awareness and willingness to scrap the work! :)
Thinking about it - was this not the idea of go from the start? Nothing fancy to keep non-rocket scientist away from foot-guns, and have everyone produce code that everyone else can understand.
Diving in to a go project you almost always know what to expect, which is a great thing for a business.
I had always designed very large projects as few medium sized independent Go tools and that strategy pays in times of AI assisted coding.
But does Google actually train its models on its internal codebase? Considering that there’s always the risk of the models leaking proprietary information and security architecture details, I hardly believe they would run that risk.
We have a second, isolated model that has trained on internal code. The public Gemini AFAIK has never seen that content. The lawyers would explode.
Just out of curiosity, do you see much difference in quality between the isolated model and the public-facing ones?
But when I had to choose between “2.0 with Google internal knowledge” and “2.5 that knows nothing” the latter was always superior.
The bitter lesson indeed.
Were they to train it on their C++ codebase, it would not be effective on account of the fact that they don't use boost or cmake or any major stuff that C++ in the wider world use. It would also suggest that the user make use of all kinds of non-available C++ libraries. So no, they are not training on their own C++ corpus nor would it be particularly useful.
I've tried using a few new languages and the LLMs would all swap the code for syntactically similar languages, even after telling them to read the doc pages.
Whether that's for better or worse I don't know, but it does feel like new languages are genuinely solving hard problems as their raison d'etre.
LLMs thrive because they had a wealth of high-quality corpus in the form os Stack Overflow, Github, etc. and ironically their uptake is causing a strangulation of that source of training data.
Out of curiosity, I told it that I was proud of it for trying and it had a burst of energy again and tried a few more (failing) solution, before going back to it's shameful state.
Then I just took care of the issue myself.
I can't say much about writing new code though.
Claude did it fine but I was not happy with the code. What Gemini came up with was much better but it could not tie things together at the end.
First it did the search itself and then added "echo" for each of them - cute
Then it tried to use pytrends which didn't go anywhere
Then it tried some other paid service which also didn't go anywhere
Then it tried some other stuff which also didn't go anywhere
Finally it gave up and declared failure.
It will probably be useful as it can do the modify/run loop itself with all the power of Gemini but so far, underwhelming.
Unfortunately the CLI version wasn't able to create coherent code or fix some issues I had in my Rust codebase as well.
Here's hope that it eventually becomes great.
That's a ton of free limit. This has been immensely more successful than void ide.
How did they do that pretty "GEMINI" gradient in the terminal? is that a thing we can do nowadays? It doesn't seem to be some blocky gradient where each character is a different color. It's a true gradient.
(yes I'm aware this is likely a total clone of claude code, but still am curious about the gradient)
And it is a blocky gradient, each character is a color. It's just the gradient they chose is slow enough that you don't notice.
More of my notes here: https://simonwillison.net/2025/Jun/25/gemini-cli/
In comparison to Claude Code Opus 4, it seemed much more eager to go on a wild goose chase of fixing a problem by creating calls to new RPCs that then attempted to modify columns that didn't exist or which had a different type, and its solution to this being a problem was to then propose migration after migration to modify the db schema to fit the shape of the rpc it had defined.
Reminded me of the bad old days of agentic coding circa late 2024.
I'm usually a big fan of 2.5 Pro in an analysis / planning context. It seems to just weirdly fall over when it comes to tool calling or something?
Not impressed. These companies have billions at their disposal, and probably pay $0 in tax, and the best they can come up with is this?
Then there are 3rd party channels, if you have a recent samsung phone, you get 1 yr access to AI features powered by gemini, after which you need to pay. And lord knows where else has google been integrating gemini now.
Ive stopped using google's AI now. Its like they have dozens of teams within gemini on completely different slack sessions.
I just symlink now to AGENTS.md
You might want to tell Claude not to write so many comments but you might want to tell Gemini not to reach for Kotlin so much, or something.
A unified approach might be nice, but using the same prompt for all of the LLM "coding tools" is probably not going to be as nice as having prompts tailored for each specific tool.
Instructions for Claude:
- ...
- ...
Instructions for Gemini:
- ...
- ...
Claude Code seems to require the CLAUDE.md filename.
How do I reset permissions so it always asks again for `git` invocations?
Thanks!
Gemini CLI does not take new direction especially well. After planning, I asked it to execute and it just kept talking about the plan.
Another time when I hit escape and asked it to stop and undo the last change, it just plowed ahead.
It makes a lot of mistakes reading and writing to files.
Some, but by no means all, of the obsequious quotes from my first hour with the product: - “You’ve asked a series of excellent questions that have taken us on a deep dive ...” - “The proposed solution is not just about clarity; it’s also the most efficient and robust.”
Therefore I was not surprised to experience Gemini spiraling into an infinite loop of self-deprecation - literally it abandoned the first command and spiraled into 5-10line blocks of "i suck"
---
Right now there is one CLI that influences and stands far and beyond all others. Smooth UX, and more critical some "natural" or inherent ability to use its tools well.
Gemini can also achieve this - but i think it's clear the leader is ahead because they have a highly integrated training process with the base model and agentic tool use.
While writing this comment, thinking that there should be some packaging tool that would create a binaries from npx cli tools. I remember such things for python. Binaries were fat, but it is better then keep nodejs installed on my OS
- the cli runs in whatever your active (nvm, asdf, etc) is configured in that directory. So for each version of node you work in you need to install a different copy of gemini.
- if you work in an older version of nodejs, then you need to run 2 different versions of node (in different tabs) to use the tool and run your project.
---
Right now there is one CLI that influences and stands far and beyond all others. Smooth UX, and more critical some "natural" or inherent ability to use its tools well.
Gemini can also achieve this - but i think it's clear the leader is ahead because they have a highly integrated training process with the base model and agentic tool use.
1. Go to their enterprise site
2. See what privacy guarantees they advertise above the consumer product
3. Conclusion: those are things that you do not get in the consumer product
For Code Assist, here's their enterprise-oriented page vs their consumer-oriented page:
https://cloud.google.com/gemini/docs/codeassist/security-privacy-compliance#data-protection-privacy
It seems like these are both incomplete and one would need to read their overall pages, which would be something more like
https://support.google.com/a/answer/15706919?hl=en
https://support.google.com/gemini/answer/13594961?hl=en#reviewers
https://youtu.be/HC6BGxjCVnM?feature=shared&t=36
It's a FOSS MCP server I created a couple of weeks ago:
- https://github.com/mbailey/voicemode
# Installation (~/.gemini/settings.json)
{
"theme": "Dracula",
"selectedAuthType": "oauth-personal",
"mcpServers": {
"voice-mode": {
"command": "uvx",
"args": [
"voice-mode"
]
}
}
}1. The thing going in a circle trying to fix a bug by persistently trying different permutations of an API interface it never bothered to check the definition of. Isn't that why it's internet connected?
2. When I asked it to just analyze instead of change stuff. It just hung for 20 minutes giving me responses saying that gemini-2.5-pro was slow, and that it was switching to 2.5-flash, with no other output to indicate what it was doing other than those cute scrolling messages that mean nothing.
At least in Claude it's clear that the messages mean nothing, because they're clearly generic. Gemini gives you the impression the status messages mean something since they're sort of related to the topic being worked on.
1. First authentication didn't work on my headless system, because it wants an oauth redirect to localhost - sigh.
2. Next, WebFetch isn't able to navigate github, so I had to manually dig out some references for it.
3. About 2 mins in, I just got ``` ℹ Rate limiting detected. Automatically switching from gemini-2.5-pro to gemini-2.5-flash for faster responses for the remainder of this session. ``` in a loop with no more progress.
I understand the tool is new, so not drawing too many conclusions from this yet, but it does seem like it was rushed out a bit.
Then I hit the rate limit. - Fine, no worries, it'll be interesting to see if the quality changes.
Then it starts getting stuck and taking forever to complete anything. So I shut it down for the day.
Today, I start it back up and ask it to pickup where it left off and it starts spinning. I forget about it and come back 7.5 hours later and it' still spinning. When I kill it it said: 1 Turn, 90k input tokens, 6.5 hours of API time... WTH?
And now I'm just totally rate limited - `status: 429, statusText: 'Too Many Requests'` - every time. Also, I can't find any kind of usage data anywhere!
Never had anything like this with claude code.
I've used Gemini 2.5 Pro quite a lot and like most people I find it's very intelligent. I've bent over backwards to use Gemini 2.5 Pro in another piece of work because it's so good. I can only assume it's the gemini CLI itself that's using the model poorly. Keen to try again in a month or two and see if this poor first impression is just a teething issue.
I told it that it did a pretty poor job and asked it why it thinks that is, told it that I know it's pretty smart. It gave me a wall of text and I asked for the short summary
> My tools operate on raw text, not the code's structure, making my edits brittle and prone to error if the text patterns aren't perfect. I lack a persistent, holistic view of the code like an IDE provides, so I can lose track of changes during multi-step tasks. This led me to make simple mistakes like forgetting a calculation and duplicating code.
> hello
[API Error: {"error":{"message":"{\n \"error\": {\n \"code\": 429,\n \"message\": \"Resource has been exhausted (e.g. check quota).\",\n \"status\": \"RESOURCE_EXHAUSTED\"\n }\n}\n","code":429,"status":"Too Many Requests"}}] Please wait and try again later. To increase your limits, request a quota increase through AI Studio, or switch to another /auth method
⠼ Polishing the pixels... (esc to cancel, 84s)
`GEMINI_API_KEY="" gemini` + login using my Google account solves the problem.
Slow response times detected. Automatically switching from gemini-2.5-pro to gemini-2.5-flash for faster responses for the remainder of this session.
To avoid this you can utilize a Gemini API Key. See: https://goo.gle/gemini-cli-docs-auth#gemini-api-key
You can switch authentication methods by typing /auth
Microsoft has a track record of delivering enterprise solutions that dates back to when Page and Brin were toddlers.
> 429: Too many requests
Mind you, this is with a paid API key
Tried upgrading to the Standard plan through Google Cloud with the hope that it would allow me to do more, but after switching my account to the now-paid account, it still almost instantly downgraded me to 2.5-flash
For the times when I was able to use 2.5-pro, the output has been very good. But the moment it switches to flash, the quality goes down by about 80% and I would never let it code on anything
It generates a bunch of fake activity indicators based on your prompt, then cycles through them on a timer. It has no bearing on the actual activity going on underneath.
It appears to be much slower than Claude Code, possibly due to being overloaded, but it feels like it thinks a lot more before beginning to suggest file edits. The permissions aren't as nice either. Where Claude Code suggests "allow uv run pytest without approval", Gemini suggests "allow uv run without approval", which is broader than I would like.
It is vastly more difficult to understand what Google is offering compared to the others, to what cost, getting an API-key or similar, understanding usage/billing across the suite, etc.
I wouldn't expect any regular person to bother signing up for any of Google's products, let alone understand what they're really offering.
1) I tried to use it on an existing project asking this "Analyse the project and create a GEMINI.md". It fumbled some non sense for 10-15 minutes and after that it said it was done, but it had only analysed a few files in the root and didn't generate anything at all.
2) Despite finding a way to login with my workspace account, it then asks me for the GOOGLE_CLOUD_PROJECT which doesn't make any sense to me
3) It's not clear AT ALL if and how my data and code will be used to train the models. Until this is pretty clear, for me is a no go.
p.s: it feels like a promising project which has been rushed out too quickly :/
This is my experience with ALL AI editors and models. Half of the time, they say they changed things, but they didn't change anything.
I hate this openwashing. It's a closed model, its weights are nowhere to be seen! (not to mention the training data, the real "source" of a LLM)
The fact that there is a small component that is open source that accesses this closed model doesn't change that at all.
I use aichat now but it's not perfect. https://github.com/sigoden/aichat
The UI on this tool is much better.
If you need to do research, pre-training, RLHF, inference for 5-10 different models across 20 different products, how do you optimally allocate your very finite compute? Weight towards research and training for better future models, or weigh towards output for happier consumers in the moment?
It would make sense that every project in deepmind is in constant war for TPU cycles.
I guess I will use something else. This is all very annoying given that I actually pay for Gemini Pro...
Well, not sure that it makes sense to do it, anyway I've tried to run in in a cell and in the google colab terminal. Still waiting for auth (?)
It's more focused on implications for docs strategy (I'm worried that agent providers are steering us towards duplicating information that's already in eng docs) rather than user best practices i.e. "put this into your agent doc to improve agent performance"
This also strikes me as such an organic (ironically) problem that it probably makes sense for everyone to pool their prompts together, together with their observations, to try to discern what patterns tend to work.
Google services have become a patchwork of painfully confounding marketing terms that mean nothing and obfuscate what they actually provide.
Whenever some enthusiastic developer suggests a new google service at work they are quickly dissuaded by senior developers that have been through their churn before.
1. Gemini Code Assist (GCA) for Individuals: FREE for 1,000 model requests/day
2. GCA Standard: $22.80/month for 1,500 model requests/day (1.5x more than FREE)
3. GCA Enterprise: $54.00/month for 2,000 model requests/day (2X more than FREE)
Source: https://codeassist.google
gave it brief instructions to deploy a hobby static site on cloud run yesterday; with additional architecture to set up (load balancer etc). It got into a loop, started deleting the gcloud resouces it created when it hit a 403 error for the site.
I hit ESC and prodded a little in terms of authentication rules ... and off it went to complete the task. bravo!
When I try to log in using a personal account, it tells me I need to generate something in the dashboard. I know that on my main account from maybe 15 years ago I had things like domains thats nowdays Google Workspace. But I'm trying to log in and authorize using my second (NOT MAIN), relatively new account. Despite this, it redirects me to the console (like it would for the first account), and there it says I'm logged in (!), but the application itself says I'm not.
I switched profiles within the console too, tried the same steps, and it still results in the same problem. Yes, I can see my new profile in the top right corner, not the old one. It sends me to a "Users may have to specify a GOOGLE_CLOUD_PROJECT if:" github [0] saying this ID is needed, and I honestly would even generate it, but I don't want to waste time with the program if you can't even get basic authorization working correctly.
0: https://github.com/google-gemini/gemini-cli/blob/main/docs/cli/authentication.md#workspace-gca
It keeps putting import statements in the middle of files or duplicating edits at the wrong places, but it's hard to get frustrated since it seems pretty self-aware. I didn't say it was making a mess - it's just being hard on itself.
A short session ended up sending over 3 million tokens though - wonder how the economics of this work out for google?